New Sensor Concept for High Precision Angle and Rotational Speed Measurements

Due to the growing demand for efficient and sustainable transportation, various research topics in the field of Electric Vehicles (EVs) have attracted more attention over the past decades. EVs are becoming increasingly popular due to their higher acceleration rates, smooth and quiet operation, and can be conveniently charged at home, unlike vehicles with combustion engines. For the smooth and efficient operation of electrical machines, precise information about the rotor position and speed is crucial. This thesis presents a novel approach based on multifunctional sensors for the estimation of the rotor speed and position to make them ready for use in electrical machines as efficient, small, and inexpensive rotor position sensors, particularly in EV applications. This sensor, which indeed is a Flexible Printed Circuit (FPC) that is mounted on the stator tooth within the air gap of an electric machine. In this way, it facilitates the evaluation of different electromagnetic qualities such as the flux linkage in the air gap, rotor position and speed, the stator temperature, and machine torque. The proposed algorithm is designed to deal with several challenges, including the accurate and reliable estimation of parameters in real-time, taking into account the effects of speed and current changes, even in the high-speed range. In this proposed algorithm, based on the detection of periodically occurring peaks of the induced voltage generated across each FPC coil, the frequency and consequent rotational speed are calculated. Moreover, a Sliding Mode Angle Tracking Observer (SM-ATO) estimates the preliminary rotor position. In particular, a novel neural network-based compensation technique is introduced to handle current dependency deviations in the estimated angle, ensuring accurate rotor position detection even under different load conditions. The presented algorithm is first examined on a modeled closed-loop system under various error scenarios. The robustness as well as the potential effects of such error scenarios on the resulting estimation parameters are analyzed, and the limit range of the estimation parameters is determined, the exceeding of which can lead to instability of the control loop. Subsequently, the presented methodology is implemented on a dSPACE device for experimental validation using a Permanent Magnet Synchronous Machine (PMSM) test bench. The algorithm's performance is examined under various operational conditions, including different speeds, torque levels, as well as different rates of change of these parameters, but also operating temperatures. Both simulation and experimental results demonstrate the accuracy, reliability, and robustness of the estimation of the rotor position and speed, and thus also the performance of the proposed algorithm. Therefore, it is confirmed that the proposed methodology has the potential for practical application in electric vehicles, highlighting its ability to enhance the performance, efficiency, and reliability of electric machine control.